Towards distributed geolocation by employing a delay-based optimization scheme

Abstract

To support position-dependent services, like matchmaking algorithms for online games or geographic backup routes, the estimation of peer locations became a key requisite for a range of applications, recently. However, exact localization may be impossible, e.g., due to nodes lacking Global Positioning System (GPS) access for reasons of cost, energy, or signal unavailability. Alternative approaches, e.g., by nearby WLAN BSSIDs or IP geolocation, rely on databases and normally contain large outliers, in particular when concerning underrepresented mapping locations. This led us to the study of a complementary idea: By embedding nodes on a sphere and periodically minimizing local positioning errors by delay-based multilateration, we efficiently estimate node positions by distributed means, given a fair amount of position hints. Based on simulations that rely on real-world PlanetLab latency data, we show that global-scope peer locations can be estimated with an accuracy of a few hundred kilometers, where the novel approach outperforms a previously proposed spring-mass-based method by about 50%.

Revisiting the Privacy Implications of Two-Way Internet Latency Data

“…Indeed, this underpins the provision of location-based services. Latency has been used to improve IP geolocation accuracy [10][11][12], and uncover potential fraud [13].…”

ImMuNE: Improved Multilateration in Noisy Environments

“…Other works do not work on the global scale because they need close landmarks [17] [18], sometimes inside the very city of the target, whereas our landmarks can be all over the world. The further away the landmarks are, the larger the RTT will be, and the more cumulative the error will be.…”